{"id":"https://openalex.org/W3097297000","doi":"https://doi.org/10.3390/s20216204","title":"An Efficient Residual-Based Method for Railway Image Dehazing","display_name":"An Efficient Residual-Based Method for Railway Image Dehazing","publication_year":2020,"publication_date":"2020-10-30","ids":{"openalex":"https://openalex.org/W3097297000","doi":"https://doi.org/10.3390/s20216204","mag":"3097297000"},"language":"en","primary_location":{"id":"doi:10.3390/s20216204","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20216204","pdf_url":"https://www.mdpi.com/1424-8220/20/21/6204/pdf?version=1604997863","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/20/21/6204/pdf?version=1604997863","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010962482","display_name":"Qinghong Liu","orcid":"https://orcid.org/0000-0002-4429-7446"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghong Liu","raw_affiliation_strings":["School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China","State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China"],"affiliations":[{"raw_affiliation_string":"School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088716214","display_name":"Yong Qin","orcid":"https://orcid.org/0000-0002-6519-8316"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yong Qin","raw_affiliation_strings":["Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University, Beijing 100044, China","State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China"],"affiliations":[{"raw_affiliation_string":"Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100457298","display_name":"Zhengyu Xie","orcid":"https://orcid.org/0000-0002-7925-418X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyu Xie","raw_affiliation_strings":["Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University, Beijing 100044, China","School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China"],"affiliations":[{"raw_affiliation_string":"Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072704517","display_name":"Zhiwei Cao","orcid":"https://orcid.org/0000-0003-1611-9703"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Cao","raw_affiliation_strings":["School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China","State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China"],"affiliations":[{"raw_affiliation_string":"School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108050300","display_name":"Limin Jia","orcid":"https://orcid.org/0000-0002-1561-0405"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Limin Jia","raw_affiliation_strings":["Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University, Beijing 100044, China","State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China"],"affiliations":[{"raw_affiliation_string":"Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5088716214"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.4907,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.66886614,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"20","issue":"21","first_page":"6204","last_page":"6204"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.8353520035743713},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6112362146377563},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6071894764900208},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.600063145160675},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5021634101867676},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3350435793399811},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19814446568489075}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8353520035743713},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6112362146377563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6071894764900208},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.600063145160675},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5021634101867676},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3350435793399811},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19814446568489075}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s20216204","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20216204","pdf_url":"https://www.mdpi.com/1424-8220/20/21/6204/pdf?version=1604997863","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c827c00eae49426d81faf6e6792fae27","is_oa":true,"landing_page_url":"https://doaj.org/article/c827c00eae49426d81faf6e6792fae27","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 20, Iss 21, p 6204 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/20/21/6204/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s20216204","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 20; Issue 21; Pages: 6204","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7662381","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7662381","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s20216204","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20216204","pdf_url":"https://www.mdpi.com/1424-8220/20/21/6204/pdf?version=1604997863","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.47999998927116394,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G4702396748","display_name":null,"funder_award_id":"No. 2016YFB1200203\u201002\u201002","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3097297000.pdf","grobid_xml":"https://content.openalex.org/works/W3097297000.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W1596502142","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1803059841","https://openalex.org/W2002299629","https://openalex.org/W2028763589","https://openalex.org/W2028990532","https://openalex.org/W2035773017","https://openalex.org/W2065002911","https://openalex.org/W2097900287","https://openalex.org/W2109616376","https://openalex.org/W2114551416","https://openalex.org/W2114867966","https://openalex.org/W2121880036","https://openalex.org/W2125188192","https://openalex.org/W2125676229","https://openalex.org/W2128254161","https://openalex.org/W2128926607","https://openalex.org/W2156936307","https://openalex.org/W2194775991","https://openalex.org/W2256362396","https://openalex.org/W2331128040","https://openalex.org/W2467473805","https://openalex.org/W2519481857","https://openalex.org/W2536722097","https://openalex.org/W2560533888","https://openalex.org/W2779176852","https://openalex.org/W2791550762","https://openalex.org/W2794732983","https://openalex.org/W2796347433","https://openalex.org/W2798876216","https://openalex.org/W2802983979","https://openalex.org/W2804575354","https://openalex.org/W2810713506","https://openalex.org/W2894289548","https://openalex.org/W2912130719","https://openalex.org/W2963152299","https://openalex.org/W2963306157","https://openalex.org/W2963470893","https://openalex.org/W2963751414","https://openalex.org/W2963928582","https://openalex.org/W2968878340","https://openalex.org/W2991006905","https://openalex.org/W2998249728","https://openalex.org/W3096115256","https://openalex.org/W6631190155","https://openalex.org/W6676391317","https://openalex.org/W6687483927","https://openalex.org/W6750227808"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Trains":[0],"shuttle":[1],"in":[2,13],"semiopen":[3],"environments,":[4],"and":[5,38,85,111,122,143,161],"the":[6,14,24,28,91,128,135,148,172],"surrounding":[7,29],"environment":[8,30],"plays":[9],"an":[10,71],"important":[11],"role":[12],"safety":[15],"of":[16,23,31,56,80],"train":[17],"operation.":[18],"The":[19,54,105],"weather":[20],"is":[21,115],"one":[22],"factors":[25],"that":[26,78],"affect":[27],"railways.":[32,53],"Under":[33],"haze":[34,75],"conditions,":[35],"railway":[36,45,60,155],"monitoring":[37],"staff":[39],"vision":[40,145],"could":[41],"be":[42],"blurred,":[43],"threatening":[44],"safety.":[46],"This":[47],"paper":[48,58,69],"tackles":[49],"image":[50,62,93],"dehazing":[51,63,150],"for":[52,59],"contributions":[55],"this":[57,68],"video":[61],"are":[64],"as":[65],"follows:":[66],"(1)":[67],"proposes":[70],"end-to-end":[72],"residual":[73],"block-based":[74],"removal":[76],"method":[77,166],"consists":[79],"two":[81],"subnetworks,":[82],"namely":[83],"fine-grained":[84],"coarse-grained":[86],"network":[87],"can":[88],"directly":[89],"generate":[90,127],"clean":[92],"from":[94],"input":[95],"hazy":[96],"image,":[97],"called":[98],"RID-Net":[99],"(Railway":[100],"Image":[101],"Dehazing":[102],"Network).":[103],"(2)":[104],"combined":[106],"loss":[107,110,113],"function":[108],"(per-pixel":[109],"perceptual":[112],"functions)":[114],"proposed":[116,149],"to":[117,126,146,171],"achieve":[118],"both":[119],"low-level":[120],"features":[121,124],"high-level":[123],"so":[125],"high-quality":[129],"restored":[130],"images.":[131],"(3)":[132],"We":[133],"take":[134],"full-reference":[136],"criterion":[137],"(PSNR&SSIM),":[138],"object":[139],"detection,":[140],"running":[141],"time,":[142],"sensory":[144],"evaluate":[147],"method.":[151],"Experimental":[152],"results":[153],"on":[154],"synthesized":[156],"dataset,":[157,160],"benchmark":[158],"indoor":[159],"real-world":[162],"dataset":[163],"demonstrate":[164],"our":[165],"has":[167],"superior":[168],"performance":[169],"compared":[170],"state-of-the-art":[173],"methods.":[174]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}